The Decision Systems and e-Service Intelligence Lab is working to develop theories, methods and software systems to help organisations make better, more informed decisions and give them an edge as they chart their course through the sea of Big Data.
Associate Professor Guangquan Zhang | Lab Director
Associate Professor Yi Zhang | Lab Co-Director
Data-driven decision making through fuzzy logic and machine learning
The Decision Systems and e-Service Intelligence (DeSI) Lab is developing advanced fundamental knowledge and methodologies to effectively support data-driven or learning based decision making, and novel real-world decision support applications.
The lab's areas of research focus are transfer learning, concept drift detection and reaction, reinforcement learning, recommender systems, fuzzy decision support systems, cloud computing, intelligent bibliometrics and early warning systems.
Top left: DeSI Lab's research focus areas
Top right: Concept drift learning. Data arrives in streams that undergo constant and arbitrary distribution changes
Bottom left: Transfer learning. Leveraging knowledge acquired from the source to domain, to improve learning efficiency or solve insufficient labelled data issues in a target domain
Bottom right: Recommender systems. Providing personalised and productive experiences for the online user by processing and analysing big data sets